AI Assistant

Build Your Own Judicial AI Assistant with Anthropic's Claude

A visual representation of building an AI Judicial Assistant using Anthropic's Claude.

What Is Claude?

Claude is a powerful Large Language Model developed by Anthropic. This versatile tool is designed to serve a variety of purposes including a chatbot, summarization tool, and code-writing assistant. Recently, Anthropic announced an exciting milestone: Claude is enhancing its context size to 100,000 tokens, which is equivalent to approximately 75,000 words. This expanded capacity will significantly improve the efficiency for users working with extensive documents and literature. In the past, reviewing long texts could take up to five hours, but now Claude is capable of reading, summarizing, and analyzing these texts in just a few minutes!

One notable feature of Claude is its emphasis on user safety. Moreover, feedback indicates that interactions with this LLM feel remarkably human-like. There’s speculation that a new frontrunner in AI has emerged, potentially leading us all to integrate Anthropic applications into our daily routines.

Before we dive into the detailed functionalities of Claude, let’s explore how to utilize this robust AI tool.

How to Use Claude

To access Claude, users must apply for early access. In this tutorial, we will use the Anthropic Python SDK to streamline our experience working with the model. Alternatively, developers can utilize the API or TypeScript/JavaScript SDK.

Legal Tech - AI for Law

In the intricate sector of legal affairs, the ability to accurately analyze and interpret legal documents is crucial. The standardized language and length of such documents often render the process tedious and time-consuming. Anthropic's Claude provides a promising solution by swiftly analyzing extensive legal texts, offering pertinent information, and generating comprehensive insights—including potential impacts, sentiments, repercussions, and possible pitfalls in legal clauses, like those in contracts.

What we aim to explore here is not just the common capabilities of summarization and prediction, but Claude’s fundamental architecture as a Constitutional AI, and its proficiency in navigating large, complex prompts.

What Are We Building?

In short, we will create a simple API that leverages the claude-v1-100k model to extract information from these large prompts.

Files

Ideally, we would incorporate a legal database for querying, or a more sophisticated search interface for enhanced automation. For brevity, however, we will work with local files available in our working directory. Initially, we will use .pdf files with token counts ranging from 40,000 to 80,000. Please feel free to test the model's limits as Claude-v1-100k can handle larger inputs!

Dependencies

First, let’s create a new directory and set up a virtual environment. For this tutorial, we will need the PyPDF2 and Anthropic SDK. Additionally, we can deploy this setup on a FastApi server. Let's add these dependencies!

Scaffolding Our API

Now it’s time to import the necessary libraries. Ensure you have your API Key obtained from your early access application.

Usage

We will first define our functions to read the PDF file and utilize Claude to analyze the document. We will also create an output structure for streamlined information extraction from the response.

Let’s create a function that analyzes a legal case from a given PDF file by providing the file path, reading its content, checking the text length, and sending it to the API for analysis.

Do note that we structured our prompt using XML tags for clarity and customization. Our stop token is: \n\nHuman.

Once everything is in place, we will set up a quick endpoint to invoke this function.

Running the Server

After running our server, navigate to your localhost to test the API via Swagger.

Results

We can stop here, but as a bonus, let’s create another endpoint that can scan research papers and deliver a TL;DR version of essential findings. This serves as a practical exploration of how to effectively influence Claude’s prompts.

Simply define a new prompt and a new endpoint, and you’re ready to test!

If you would like to explore more use cases, here are some homework ideas:

  • Create a 'healthy and safe' News Digest using an RSS feed from a dubious media outlet.
  • Identify loopholes in complex contract language.
  • Compose child-friendly stories from song lyrics.

These tasks can help enlighten your experience with Anthropic and how to better engage with Claude!

Conclusion

In summary, we have succeeded in gaining insight into a comprehensive legal case with over 100 pages in mere seconds. This illustrates that Anthropic's Claude is fully equipped to manage extensive texts efficiently. Further exploration could involve generating summaries of court case developments and pinpointing key arguments.

For those interested in building their own Anthropic application, an exciting opportunity to skip the waitlist is on the horizon! If you are part of the lablab.ais community and signed up for the Anthropic Hackathon before May 23, follow our detailed guide to access the Anthropic Claude API ahead of others.

If you didn’t get access this time, stay tuned for more AI hackathons, as we have thrilling events planned for our incredible community!

다음 보기

A screenshot of Shap-E generating 3D models in Google Colab.
A visual guide to building an AI chatbot using Anthropic's Claude.

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